Jordan D. Fuhrman

According to our database, Jordan D. Fuhrman authored at least 10 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Multi-institutional development and testing of attention-enhanced deep learning segmentation of thyroid nodules on ultrasound.

Joseph L. Cozzi, Hui Li, Jordan D. Fuhrman, Li Lan, Jelani Williams, Brendan Finnerty, Thomas J. Fahey, Abhinay Tumati, Joshua Genender, Xavier M. Keutgen, Maryellen L. Giger

Int. J. Comput. Assist. Radiol. Surg., February, 2025

2023

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx.

Trung-Hieu Hoang, Jordan D. Fuhrman, Ravi K. Madduri, Miao Li, Pranshu Chaturvedi, Zilinghan Li, Kibaek Kim, Minseok Ryu, Ryan Chard, Eliu A. Huerta, Maryellen L. Giger

CoRR, 2023

Assessing an AI-based smart imagery framing and truthing (SIFT) system to assist radiologists annotating lung abnormalities on chest x-ray images for development of deep learning models.

Lin Guo, Kunlei Hong, Ziqi Zhang, Bin Zheng, Stefan Jaeger, Jordan D. Fuhrman, Hui Li, Maryellen L. Giger, Andrei Gabrielian, Alex Rosenthal, Darrell E. Hurt, Ziv Yaniv, Y. M. Fleming Lure

Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service.

Zilinghan Li, Shilan He, Pranshu Chaturvedi, Trung-Hieu Hoang, Minseok Ryu, Eliu A. Huerta, Volodymyr V. Kindratenko, Jordan D. Fuhrman, Maryellen L. Giger, Ryan Chard, Kibaek Kim, Ravi K. Madduri

Proceedings of the 19th IEEE International Conference on e-Science, 2023

2021

Application and generalizability of U-Net segmentation of immune cells in inflamed tissue.

Rebecca Abraham, Madeleine S. Durkee, Margaret Veselits, Junting Ai, Jordan D. Fuhrman, Marcus R. Clark, Maryellen L. Giger

Proceedings of the Medical Imaging 2021: Digital Pathology, Online, February 15-19, 2021, 2021

Radiomic texture analysis for the assessment of osteoporosis on low-dose thoracic CT scans.

Jordan D. Fuhrman, Linnea Kremer, Yeqing Zhu, Rowena Yip, Feng Li, Li Lan, Hui Li, Artit C. Jirapatnakul, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Comparison of 2D and 3D U-Net breast lesion segmentations on DCE-MRI.

Roma Bhattacharjee, Lindsay Douglas, Karen Drukker, Qiyuan Hu, Jordan D. Fuhrman, Deepa Sheth, Maryellen L. Giger

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2020

Effect of observer variability and training cases on U-Net segmentation performance.

Jordan D. Fuhrman, Peter Halloran, Rowena Yip, Artit C. Jirapatnakul, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger

Proceedings of the Medical Imaging 2020: Image Perception, 2020

Cascade of U-Nets in the detection and classification of coronary artery calcium in thoracic low-dose CT.

Jordan D. Fuhrman, Rowena Yip, Artit C. Jirapatnakul, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019

Detection and classification of coronary artery calcifications in low dose thoracic CT using deep learning.

Jordan D. Fuhrman, Jennie Crosby, Rowena Yip, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019